Thermal powerline rating and clearance analysis using thermal imaging technology

ABSTRACT

A method and apparatus are provided to acquire direct thermal measurements, for example, from a LiDAR collecting vehicle or air vessel, of an overhead electrical conductor substantially simultaneous with collection of 3-dimensional location data of the conductor, and utilize temperature information derived from the direct thermal measurements in line modeling, line rating, thermal line analysis, clearance analysis, and/or vegetation management.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. Ser. No.13/212,684 filed Aug. 18, 2011, which is related to commonly assigned,U.S. Ser. No. 13/212,689, filed Aug. 18, 2011, and claims priority ofU.S. provisional application Ser. No. 61/426,037 filed on Dec. 22, 2010,Ser. No. 61/448,236 filed on Mar. 2, 2011, and Ser. No. 61/495,694 filedon Jun. 10, 2011, the entire contents of these applications being herebyincorporated by reference herein.

BACKGROUND

This invention relates generally to the field of powerline management,and, more particularly to a new approach that directly determinestemperature of an overhead electrical conductor at time of 3-dimensionallocation data collection, for use in such applications as CAD modelingof the conductor, thermal line analysis of the conductor, thermal ratingof a power line that includes the conductor, clearance analysis relativeto the conductor, vegetation management relative to the conductor,and/or other applications especially useful to electric utilities insafeguarding and optimizing their transmission and distributioninfrastructure.

LiDAR (Light Detection And Ranging) is used to produce CAD (ComputerAssisted Design) models of powerlines. In the process known to industry,LiDAR data is collected using a sensor that is mounted to an aerialplatform, tripod or a land vehicle. For clearance analysis duringdifferent conductor conditions, it is important to know the temperatureat the time the LiDAR data was collected. In the process known toindustry, LiDAR data is captured simultaneously with weather and lineloading data that allows modeling of the conductor temperature.

The process of predicting conductor temperature at time of LiDAR datacollection using loading and weather data requires accurate knowledge ofweather conditions at the right-of-way. Especially, prediction of windspeed and direction are difficult to perform due to turbulence and highvariation of wind speeds. Weather stations have to be employed toacquire the weather information.

The U.S. government is currently mandating modernization of the nation'selectrical grid in order to enhance national security. As part of thiseffort, the North American Electric Reliability Corporation(NERC)—certified by the Federal Energy Regulatory Commission to developand enforce reliability standards for the electric grid in NorthAmerica—on Oct. 7, 2010 issued a regulatory alert requiring alltransmission line operators to assess within the next three years theprecise physical characteristics of their high voltage transmissionlines relative to design specifications. NERC recommended that utilitiesuse PLS-CADD (engineering software that determines what the wire'sphysical properties are and where the conductor is located under givenconditions, based on temperature and conductor type inputs) to complywith this requirement. The actual conductor temperature will be aleading indicator for NERC.

Current industry practice calculates—rather than measures—thetemperature of a bare conductor, utilizing factors such as ambientweather conditions, physical and thermal properties of the conductor,and line loading information. Due primarily to weather variables, thispractice can generate a significant margin of error. The associateduncertainty of a conductor's temperature directly limits its capacity.

The power conductors of overhead transmission lines are self-supportingand energized at high voltage. As current flow through conductorsincreases, the temperature of the conductors increases, causing them toelongate. This elongation increases the sag of the conductors betweensupport points, decreasing the clearance between the conductors andpeople, the ground, vegetation, buildings, vehicles and other objectsunder the lines. Beyond certain “maximum allowable” sag, the lines mayflashover, resulting in a power supply outage or injury to the public orproperty damage. Additionally, if conductor temperature remains high foran extended period of time, the strength of the conductors and tensionedconnectors may decrease, which could trigger mechanical failure duringthe next occurrence of ice or high wind loading. To avoid excessive sagor loss of strength, limits are placed on maximum operating temperatureof the conductor.

SUMMARY

Direct contemporaneous thermal measurements, e.g., from theLiDAR-collecting vehicle or air vessel, would bypass many of the currentconstraints. Accordingly, a method is presented to acquire directthermal measurements, for example, from the LiDAR collecting vehicle orair vessel, of the conductor substantially simultaneous with collectionof 3-dimensional location data of the conductor, and utilize temperatureinformation derived from the direct thermal measurements in linemodeling, line rating, thermal line analysis, clearance analysis, andvegetation management.

According to the present invention, a method is provided for thermalline analysis of an overhead electrical conductor, comprising:collecting 3-dimensional location data of the conductor; substantiallysimultaneous with said collecting, acquiring a thermal measurement ofthe conductor; generating a CAD model of the conductor using thecollected 3-dimensional location data of the conductor and the thermalmeasurement of the conductor, and employing the CAD model for thermalline analysis of the conductor.

The thermal measurement may comprise a remotely collected thermal image.The remotely collected thermal image may comprise thermal image frames,and the method may further comprise: selecting, for processing, framesof said thermal image frames that meet the following criteria: containthe conductor, contain a background having lower thermal values than theconductor, and exhibit image quality that allows accurate thermalreading. The selecting may involve automatic thermal image filtering,including at least one of: discarding image frames that have an imagesharpness index below a given threshold, discarding image frames thathave a background thermal emission higher than a thermal emission of theconductor, and selecting only image frames that contain the conductor.

The method for thermal line analysis may further include linking aselected image frame to a geographic location, by, for example,geocoding the selected frame to attribute a spatial reference and imageresolution parameters to the selected frame. Other known techniques forlinking image frames to geographic location may also be employed.

The method for thermal line analysis may further include extracting athermal reading from the geographically linked selected frame, anddetermining emitted energy from the conductor employing the extractedthermal reading.

When remote collection of the thermal image employs a thermal camerasystem, the method may further comprise radiometrically calibrating thethermal camera system to cover an expected operational temperature rangeof the conductor.

In the method for thermal line analysis, acquiring the thermalmeasurement of the conductor substantially simultaneous with thecollecting of the 3-dimensional location data may comprise acquiring thethermal measurement at the same time that the 3-dimensional locationdata is collected or within a time period that temperature of theconductor is unlikely to vary, e.g. within fifteen minutes of thecollecting of the 3-dimensional location data.

The method for thermal line analysis may further include performing athermal analysis of the thermal measurement to determine temperature ofthe conductor at the time of collecting the 3-dimensional location data;generating the CAD model of the conductor using the temperature of theconductor determined by the thermal analysis; and employing the CADmodel of the conductor to determine a thermal rating of a target linethat includes the conductor and/or to analyze clearance between theconductor and surroundings of the conductor. The clearance analysis maycomprise conducting at least one of a sway analysis and a sag analysisto determine conductor location in different weather and/or line loadingconditions.

In the method for thermal line analysis, the 3-dimensional location datamay comprises LiDAR data collected from an airborne or other vehicle,and the thermal measurement may advantageously be acquired by thevehicle concurrently with the LiDAR data.

A method is also provided for determining temperature of an overheadelectrical conductor, comprising: collecting 3-dimensional location dataof the conductor; substantially simultaneous with said collecting,acquiring a thermal measurement of the conductor; and performing athermal analysis of the thermal measurement to determine temperature ofthe conductor at the time of collecting the 3-dimensional location data.The method may further comprise generating a CAD model of the conductorusing the collected 3-dimensional location data of the conductor and thedetermined temperature of the conductor, and employing the CAD model forat least one of: thermal line analysis of the conductor, thermal ratingof a power line that includes the conductor, clearance analysis relativeto the conductor, and vegetation management relative to the conductor.

A method is further provided for modeling of an overhead electricalconductor, comprising: collecting 3-dimensional location data of theconductor; substantially simultaneous with said collecting, acquiring athermal measurement of the conductor; and generating a CAD model of theconductor using the collected 3-dimensional location data of theconductor and the thermal measurement of the conductor.

An apparatus is provided for determining temperature of an overheadelectrical conductor, comprising: a thermal sensor that captures thermalimages on a sensor cell array; optics that project a thermal image froman imaged object onto the sensor cell array; and a data processor thatextracts thermal readings from selected image frames containing theconductor captured by the thermal sensor, and processes the thermalreadings and collected 3-dimensional location data of the conductor todetermine the temperature of the conductor.

The thermal sensor may comprise an infrared camera, a thermal linescanner, or other thermal measurement device. The apparatus may furtherinclude a thermal band filter that minimizes impact of sun reflectionfrom the conductor, and/or a sky thermometer that measures atmospherictemperature in a direction that thermal radiation may be reflected fromthe conductor towards the thermal sensor, and the data processor mayemploy the measured atmospheric temperature in determining thetemperature of the conductor.

If the thermal sensor and optics are mounted to a vehicle, the apparatusmay further include a vibration isolation device that isolates thethermal sensor and the optics from vehicle vibration, or other vibrationmitigation device(s) and/or practice(s).

The apparatus may further include a LiDAR sensor or other sensorcollecting 3-dimensional location data of the conductor substantiallysimultaneous with the thermal sensor capturing thermal images of theconductor, and, optionally, a recording positioning device that recordsthermal sensor location readings for image frames of thermal imagescaptured by the thermal sensor. The data processor may further performat least one of: thermal modeling of the conductor, thermal lineanalysis of the conductor, thermal rating of a line containing theconductor, and clearance analysis relative to the conductor, based onthe determined temperature of the conductor.

An apparatus is further provided for determining temperature of anoverhead electrical conductor, comprising: a location sensor collecting3-dimensional location data of the conductor; a thermal sensor acquiringa thermal measurement of the conductor substantially simultaneous withsaid collecting; and a data processor employing the collected3-dimensional location data of the conductor and the thermal measurementto determine the temperature of the conductor at time of collection ofthe 3-dimensional location data of the conductor. The location sensormay comprise a LiDAR sensor or other location data collecting sensor,and the thermal sensor may comprise a thermal image capturing device orother thermal measurement device. A recording positioning device thatrecords thermal sensor location readings for image frames of thermalimages captured by the thermal sensor may be included in the apparatus.

The data processor of the apparatus may generate a CAD model of theconductor using the 3-dimensional location data of the conductorcollected by the location sensor, and the thermal measurement of theconductor acquired by the thermal sensor, and may also perform at leastone of: thermal modeling of the conductor, determining thermal rating ofa line containing the conductor, thermal line analysis of the conductor,and analyzing clearance between the conductor and surroundings of theconductor, based on the determined temperature.

BRIEF DESCRIPTION OF THE DRAWINGS

Various aspects, features and advantages of the present invention willbe apparent from the following detailed description of illustrativeembodiments, read in conjunction with the accompanying drawings, inwhich:

FIG. 1 illustrates an example of a thermal line analysis method usingthermal imaging technology;

FIG. 2 schematically illustrates an example of apparatus that may beused in implementing the thermal line analysis method;

FIG. 3 illustrates basic components of a typical thermal imaging device;

FIG. 4 is a simplified flow chart of steps of the method;

FIG. 5 illustrates operation of a conductor detection filter;

FIG. 6 illustrates a thermal detection window placed on a conductor andturned to follow the conductor direction; and

FIG. 7 is a graph illustrating temperature estimation error as afunction of difference between sky temperature and conductortemperature.

DETAILED DESCRIPTION

FIG. 1 provides an overview of a method for thermal line analysis of anoverhead electrical conductor in accordance with the principles of thepresent invention. The method may include the following steps.

LiDAR Data Collection of a Powerline (10)

Collecting LiDAR data over a powerline is a process well known to theindustry.

Simultaneous Thermal Image Collection Covering the Conductor(s) (12)

Simultaneous collection of thermal measurements of the conductortemperature may be accomplished according to the process described indetail below.

Thermal Analysis to Determine the Conductor Temperature (14)

Thermal analysis to determine the conductor temperature may beaccomplished according to the process described in detail below.

LiDAR Return Classification (16)

LiDAR return classification is a process well known in the industry todetermine the type of object each return was reflected from. There arecommercial products, for example, TerraScan® software, available fromTerrasolid Ltd., Ylistönmäentie 26 A313, Fin 40500 Jyväskylä, Finlandand Merrick MARS® software, available from Merrick & Company, 2450 SouthPeoria Street, Aurora, Colorado 80014, that can be used to classify thereturns.

CAD Modeling of the Conductor(s), Using the Line Temperature at Time ofCollection from Thermal Analysis (18).

CAD modeling of line conductors itself is a process well known to theindustry. For example, commercially available PLS-CADD® softwarepackage, available from Power Line Systems, 610 N. Whitney Way, Suite160, Madison, Wis. 53705, can be used to model line conductors withLiDAR data.

Thermal Line Analysis Employing the CAD Model of the Conductor(s) (20)

In this document, the term “thermal line analysis” connotes analysisthat is done using a CAD model of the line, and simulating lineconditions under different temperatures of the conductors or other linecomponents. One type of thermal line analysis, known as Survey PointClearance (SPC) analysis, includes a clearance analysis that checks therequired horizontal and vertical clearances of each classified surveypoint in relation to the displaced conductor. In this document, surveypoint means a feature in the proximity of the line, that is of interestfor line management, and whose location is surveyed. In Survey PointClearance analysis, the conductor locations are simulated under varyingconditions, based on different combinations of wind, ice, and operatingtemperature and the clearance margin, location, and survey feature typeof each point-of-interest is recorded. The final product can be, forexample, the identification of survey features that have breached therequired clearance distances under client specified conductorconditions. Thermal Line Analysis and Survey Point Clearance analysiscan be performed, for example, within commercially available PLS-CADD®software package, available from Power Line Systems, 610 N. Whitney Way,Suite 160, Madison, Wis. 53705.

In Some Embodiments, Either of the Systems May Perform a Sag and SwayAnalysis 22 to Determine the Conductor Location in Different WeatherConditions.

Sag and sway analyses are processes well known to the industry. Forexample, commercially available PLS-CADD® software package, availablefrom Power Line Systems, 610 N. Whitney Way, Suite 160, Madison, Wis.53705, can be used to perform sag and sway analysis to determineconductor location in different weather conditions. This analysis is notnecessary, if the clearances are analyzed as observed-conditions.However, even using as observed-conditions, it is useful to record whatthe conductor temperature was during analysis.

Clearance Analysis Against Different Classes of LiDAR Data (24)

Clearance analysis is a process well known to the industry. In clearanceanalysis, the LiDAR returns in one or several classes are selected andsmallest distance between the LiDAR return and the target line iscalculated. Then, all the points where the distance is less than a givenclearance criteria for the given point class are reported. For example,commercially available PLS-CADDY software package, available from PowerLine Systems, 610 N. Whitney Way, Suite 160, Madison, Wis. 53705, can beused to perform this task.

Thermal Rating of Line Including Conductor (26)

The Thermal Line Rating (TLR) analysis determines the maximum conductortemperature that can be reached before any required clearance distancesare breached. Typically, the conductors are initially placed at 32° F.,and then heated to their maximum operating temperature (often 212° F.).At the moment that any clearance distance is breached, the conductortemperature of that span is recorded. The type and location of thecorresponding survey feature type may also be recorded. Typically, thefinal product is the maximum allowable temperature of each circuit'sspan under the existing as-found conditions. Thermal line rating can beperformed, for example, within commercially available PLS-CADD® softwarepackage, available from Power Line Systems, 610 N. Whitney Way, Suite160, Madison, Wis. 53705.

Vegetation Management (28)

Vegetation management consists of all operations undertaken to keepvegetation in proximity of a powerline, substations or other systemcomponents in a condition that does not cause harm or risk to the systemoperation, reliability or safety. Vegetation management can be planned,for example, in commercially available Powel NetBas software, availablefrom Powel, Inc., 930 Blue Gentian Road, Suite 1300, St. Paul, Minn.55121. Optionally, vegetation management can include also vegetationgrowth prediction, which is described in commonly assigned U.S. patentapplication Ser. No. 12/640,951 filed on Dec. 17, 2009, the entirecontents of which is hereby incorporated by reference herein.

An illustrative thermal image collection process and apparatus, and aprocess of thermal analysis to determine conductor temperature will nowbe described. The example presents a method and apparatus fordetermining conductor temperature from a vehicle moving or stationaryrelative to the line. The vehicle can be, for example, a helicopterflying above the lines, a ground vehicle following the line, watercraftor a ground supported stationary mount that is used to mount the thermalsensor. The thermal measurement is acquired substantially simultaneouswith line location data collection. Substantially simultaneous meanstaking the thermal measurements at the same time or within such a smalltime frame, such as 15 minutes, during which the conductor temperaturedoes not change significantly. A typical way to collect 3-dimensionalline location information is with Light Detection and Ranging sensor(LiDAR) from a helicopter, moving above the line. Although LiDAR datacollection from a helicopter is used as an example herein, fixed wingaircraft, land vehicles, spacecraft or watercraft can be used toremotely collect LiDAR or other 3-dimensional location data of utilitylines. The thermal measurement and analysis can be applied to thosecases as well.

Accordingly, a method and apparatus are provided to acquire thermalmeasurements on overhead transmission and distribution conductors attime of 3-dimensional location data (e.g. airborne LiDAR) datacollection, by thermographic imaging or other direct thermal measurementacquisition approaches. The method and apparatus may advantageously beused in overhead utility transmission and distribution power linemanagement and in overhead communication or phone line management.

System Components

An illustrative embodiment of the system or apparatus is depicted inFIG. 2 in the context of a helicopter 30 flying above one or moreoverhead electrical conductors 32 and collecting 3-dimensional locationdata (e.g., LiDAR data) with a remote location data sensor 35. Thecollection system may include, for example a main thermal sensor 34,such as an infrared camera that collects and/or measures thermalreadings on a sensor cell array. The cell array produces arrays ofpixels with thermal readings or thermal images. The sensor cells can bepositioned in a scan line as with a line scanner, or as a frame thatcontains N×M pixels as with a frame camera. The frame camera can be, forexample, based on a cooled Indium Antimonide (InSb) detector, withspectral range of 3-5 micrometer, resolution of 640×512 pixels and 15micrometer detector pitch. Integration times between 0.5-7 microsecondshave produced efficient results. FLIR® SC6700 camera available from FLIRSystems Inc. of 25 Esquire Road, North Billerica, Mass. 01862 is anexample of a commercial product that can be used. Although the use of aframe camera is described in detail herein, a line scanner can be alsoused to make thermal images that can be used in this process. Line-scanthermal imaging is known to the industry. Other thermal measurementdevices may also be employed.

FIG. 3 schematically presents basic components of a cryogenically cooledthermal imaging device, which is an efficient thermal imager for themain thermal sensor 34. Multiple other types of thermal sensors existand can provide usable thermal imagery or readings. The components shownin FIG. 3 include:

-   -   Optics 50 that transmit the image to the sensor cell 38;    -   A “Cold stop” 40 which serves as a thermal window that insulates        the cooled core but let's in the thermal radiation;    -   Cold casing 42 that insulates the cooled core;    -   Aperture 44;    -   Thermal sensor cell 38;    -   Cryogenic cooling device 46; and    -   Signal digitizer 48 that digitizes the sensor cell signal.

Operation of a thermal sensor is described hereinafter. Referring againto FIG. 2, the system components may further include optics 50 thatallow thermal signal from conductor area to be projected to the sensorcell array. The data may be projected in such a way that one sensor cellarray will record thermal information from the center part of the targetconductor. An efficient way is to record the information usingresolution that allows at least 1 complete pixel to be projected fromthe center ⅓ of the target conductor width. In typical transmissionline, this means approximately ⅓ inch resolution. An example of an opticthat might be used is a 500 mm focal length mid-wave infrared optic,with f/4. This kind of optic, matched to the FLIR® SC6700 camera, can befound for example in the FLIR® RS6701 camera package available from FLIRSystems Inc. of 25 Esquire Road, North Billerica, Mass. 01862.

Optionally, the system may contain a spectral filter 52 that allows onlya certain wavelength of thermal radiation to enter the sensor cell array[thermal band filter 52]. This filter can be used to minimize the impactof sun reflection from the conductor. Using this kind of filtering iscommon practice in thermal imaging. A suitable filter can be, forexample, 4.50 μm Infrared Longpass Filter, available from Edmund OpticsInc.—101 East Gloucester Pike, Barrington, N.J. 08007-1380 USA.Different bandwidths can be used, depending on camera sensitivity, toutilize bandwidths where sun radiation is lower intensity and wherethermal radiation can efficiently pass from the target to the camerathrough atmosphere.

Optionally, the system may contain another thermal sensor to measureatmospheric temperature, sometimes referred to in this document as a skysensor 54. The sky sensor 54 can be, for example, a thermal cameraoperating preferably on the same wavelength as the main thermal sensor,or another sensor capable of determining the relative temperature of thesky (for example, a laser thermometer). An example of a suitable thermalsensor is Jenoptik VarioTherm® LnSb 2-5 um IR camera—with 640×512 pixelsfor spectral radiometry. This camera is available from IRcameras, 1600Providence Highway, Walpole, Mass. 02081.

A recording positioning device 56 that allows recording of the mainthermal sensor location and, optionally, attitude at time of each sensorimage frame capture, may be included in the apparatus. This is used torefer the thermal images to the right coordinates in the spatialreference. The recording positioning device can be, for example, a GPS(Global Positioning System) unit. Alternatively, positioning can be doneusing the LiDAR sensor's position recording unit. In this case, timestamp of each thermal image frame is recorded. Time stamping allowslinking the image to the position recording unit's trajectory data thatrecords the sensor's position and attitude at a given time in a highfrequency. Trajectory is often recorded in 1 millisecond intervals.

Computer data storage unit (58) that stores the thermal images, skysensor readings and positioning device readings. Any known data storagedevice may be used.

Blackbody object (not shown) that can be used to radiometricallycalibrate the sensor optics assembly, as more fully describedhereinafter.

Data Processor/Computer (60) and software that runs in this dataprocessor/computer and is used to perform the data manipulation/analysisprocess described hereinafter. A suitable computer is, for example, atypical PC (Personal Computer) workstation or a laptop computer ormobile workstation computer, equipped with a program to perform themanipulation and analysis. An example of a commercially available laptopis Dell Latitude E6520, equipped with Intel® Core™ i5 2520M 2.50 GHzprocessor, 4.0 GB, DDR3-1333 MHz SDRAM memory and 320 GB 7200 rpm HardDrive, available from www.del.com.

Vibration and frequency isolation device (62). The thermal camera can beisolated from the helicopter vibration using suspended mount with somecounterweight. The camera can be tightly attached to a counterweightplate that is shaped to balance the center of gravity to the graphicalcentroid of the camera attachment points. This minimizes the rotationalvibration of the camera. Altering the total weight of the camera opticsand counterweight package, the nominal frequency of the mounted camerasystem can be set to differ from the typical main frequencies of thehelicopter vibration during thermal measurement. Alternatively, thevibration may be controlled by using motion controlled gyroscopicsystem. These systems are commercially available and represent knowntechnology.

As an example, an efficient approach is to collect the data from300-1000 ft AGL (above ground level) altitude with a sensor of 640measurement cells across the swath. The resolution at conductor levelcan be for example, ⅓ inch. This yields a swath of 17.8 ft (640*⅓ inch)at conductor level and represents approximately 1.5 degrees FOV (fieldof view) at the camera, when the collection is done from 700 ft altitudeabove the conductor.

As illustrated in FIG. 4, in a thermal imaging and analysis method, forexample, the following steps may be performed:

-   -   Camera system calibration 64;    -   Thermal imaging 66;    -   Image linking to geographic location 68, e.g. geocoding;    -   Thermal reading extraction 70;    -   Calibration measurement and temperature calculation 72; and    -   Line modeling with calculated conductor temperatures 74.

Each of these steps will now be described.

When performing camera system calibration 64, the thermal camera systemmay be calibrated to get accurate thermal readings. Thermal cameracalibration in radiometric application may account for the variablethickness of the optical material the radiation has to travel throughbefore it reaches a given sensor pixel. Additionally, imperfections inoptical material impact individual cell readings. To radiometricallycalibrate the sensor optic system a blackbody (reference source used fortesting infrared systems) is used. Infrared blackbodies are availablefrom HGH Infrared Systems, One Broadway, 1 lth Floor, Cambridge, Mass.02142 USA. The thermal camera system may be pointed to read theblackbody emission at a number of controlled temperatures and acalibration curve is fit to the readings. The calibration curve correctsthe thermal reading through each pixel so that they yield truetemperature reading from the blackbody in each temperature. Thecalibration is done so that it covers the expected temperature range ofa target conductor, for example 0-100° C. The optical system has to stayin the calibrated position for the calibration to be valid. Anytranslational and rotational dislocation of the system componentsrequires a new calibration. An efficient approach is to use a cameracalibration formula that yields a calibration curve for each pixel.

When performing thermal imaging 66, the system uses a thermal camera tocollect thermal images of an overhead conductor. In a LiDAR collectionsituation, helicopter flying precision allows the sensor path to be keptwithin a given 50-foot wide corridor. This operating accuracy of thehelicopter is called herein “helicopter operating corridor”. Because ofthe desired high resolution, the swath of the thermal camera system maybe less than the helicopter operating corridor. The term “swath” is usedherein to describe the width of the area at target level that iscaptured by the thermal sensor on one helicopter pass. The thermalsensor or camera may not always be pointed to target conductors.However, because of the high thermal conductivity of the conductormetal, (e.g., aluminum) and constant line loading in the full circuit,the inventors have found that conductor temperature stays quite constantover multiple spans that are running in same direction. This is why itis sufficient to measure the conductor temperature on the spans wherethe thermal image frames contain the conductor(s), the background isfavorable and the frame quality allows accurate thermal readings.

When the thermal sensor does not point to conductors, the backgrounddoes not allow accurate readings, or the thermal image frame has anykind of defect that may inhibit accurate thermal reading, the readingsare not taken or are discarded. To estimate conductor temperature forthe spans between the successful thermal readings, a distance-weightedmean of the closest successful neighboring readings may be used.

The certainty of capturing conductors on the thermal images may beincreased by operating the helicopter in a slightly zig-zagging course,crossing the line center frequently.

Then performing image geographic linking or geocoding 68, the thermalimages may be tied to proper locations in the spatial reference byattributing the image corner coordinates and image resolution parametersto each image. Image corner or center coordinates are given based on theGPS location of the thermal sensor 34 at time of frame exposure. Imageresolution at ground level is calculated from the FOV (Field of View)and sensor altitude AGL at time of exposure.

Alternatively, an orthoimage production process, that is well-known toremote sensing industry, can be used for image orientation. Theorthoimage production process is similar to visible band orthoimageproduction process, and can utilize the LiDAR data and the LiDAR sensortrajectory. To best utilize the LiDAR sensor trajectory, the centeroptical axis of the thermal camera can be co-aligned with the centermostLiDAR beam.

Alternatively, any other recognition technique can be used to link theacquired conductor temperature readings to corresponding spans orconductors.

The thermal reading extraction 70 process may include the followingsteps:

-   -   1. Select a thermal image frame where the image contains the        target conductor and where the background shows colder thermal        values than the conductor. For example, low vegetation often        provides a relatively stable, cool background. Optional        automatic filtering of the thermal images to avoid checking the        usability of each thermal image frame is presented below.    -   2. Select thermal detection window that contains the conductor.        In this document, thermal detection window refers to an area,        selected from a thermal image frame that is used to determine        the conductor temperature. The thermal detection window is        selected so that the conductor represents the highest emitted        thermal values in the window (Reference FIG. 5). Optionally, the        thermal detection window can be shaped as an elongated rectangle        aligned with the conductor (reference FIG. 6). An efficient way        to select thermal detection window is to use an area where the        background contains low vegetation. An efficient way to select        thermal detection window is to pre-define the desired detection        window size or window width. The user can point the camera        towards the conductor location, and the software detects the        conductor direction and places the thermal detection window on        it. The detection of conductor location can be done by selecting        the highest pixel values in the window (number of pixels to        select is set so that they cover approximate conductor area in        the thermal detection window). Selected pixel centers are turned        into a point cloud. A line is fit to the pixel center data        using, for example, smallest squares fit. The detection window        is placed to align its long main axis with the fitted line.        Alternatively, the user can point to two points on the        conductor, and the long main axis of the detection window is set        to go through the given points. Other ways of pointing to the        right location can be used. Sun reflections and potential line        hot spots, if seen on thermal image frame, are excluded from the        thermal detection window.    -   3. An efficient way is to define the thermal detection window as        a function of the conductor diameter in pixels, and make it an        elongated rectangle in conductor direction. For example, if the        conductor diameter is 1″, the pixel size is ⅓″; the thermal        detection window could be 15×60 pixels. This represents a window        that is 5 times wider than the conductor and elongated to cover        20 inches of conductor. Such a window is robust to small        inaccuracies in thermal detection window rotation errors and        cleans out most of the high thermal radiation returns from the        background.    -   4. In the detection window, the pixels that are in the middle        section of the conductor are selected. Since the conductor is        the highest emitting object in the thermal detection window, the        maximum pixel values represent the best values for conductor        temperature determination. The number of pixels to be selected        can be given as a function of the thermal detection window size.        An efficient number is, for example, one that represents that        5-20% of the visible conductor is in the thermal detection        window. FIG. 5 shows the selected highest value pixels on the        thermal detection window.    -   5. A statistic is calculated from the selected pixels to provide        W_(tot) to the temperature determination formula described        hereinafter. The statistic can be, for example, an average value        of all selected pixel values. Alternatively, more sophisticated        statistics can be used, like a given percentile of all selected        pixel values. Outlier detection can be applied to pixel values        before taking statistics.

The thermal reading may be presented to the user in a display, in adigital data or audio transmission, in a report such as a printed ordisplayed report, or any other suitable method.

As noted above, the system also may perform calibration measurement andtemperature calculation 72. The reading in main thermal sensor cell(s)is a function of the following:

-   -   W_(tot): total radiation in the pixel(s);    -   W_(obj): emitted energy from a gray body object, e.g. conductor;    -   W_(atm): emission from the atmosphere;    -   W_(amb): reflected emission from ambient sources;    -   τ: transmittance of the atmosphere; and    -   ε: object's emissivity.

These parameters are related according to the following formula:

W_(obj) can be solved from the above formula:

To calculate W_(obj), the following parameters have to be determined:

W_(tot): This value is provided as an output from thermal readingextraction process.

W_(amb): Can be determined, for example, using a recording temperaturegauge station (57) in the helicopter (30) at time of collection.Optionally, this reading can be acquired from ground-based weatherstations as well.

W_(atm): Can be determined, for example, using thermal camera that ispointed upward to the sky from collection helicopter.

τ: Is determined as a function of ambient weather conditions that arerecorded from weather station on helicopter or on the ground.

ε: Emissivity of the conductor. ε depends on the age of the conductor;especially the oxidization of the aluminum surface alters theemissivity. However, in typical line modeling situation, the conductorshave been exposed to the atmosphere so long that the oxidization hasreached a stable level and the emissivity can be considered constant fora given part of system.

The emissivity can be determined for example by painting small parts ofthe conductor with matte black paint that will alter emissivity to beapproximately 1 (1=close to blackbody). On a utility line, the paintingcan be done for example from a helicopter that performs a paintingoperation before the thermal collection. About 3-foot piece of theconductor is painted in each reference spot. A can of spray paint can beattached to a hot stick that allows painting without grounding thehelicopter to the same potential with the conductor. Alternatively, thehelicopter is grounded to the same potential with the conductor whichallows safe painting operation. Thermal readings from the paintedconductor and the adjacent non-painted part of conductor can be used todetermine the emissivity. The following formula ties the emissivity tothe emitted energy from blackbody and gray body:

ε=W _(obj) /W _(bb)  [3.]

To determine emissivity we can assume that the temperatures of theconductor of painted and adjacent non-painted parts are the same. Thisis a fair assumption because of the high heat conductivity of conductorsurface metals (aluminum, turned to aluminum oxide).

Additional verification of the proper temperature reading can be done byplacing a thermometer in or on the conductor at the time of collectionand by comparing the temperature acquired from the camera system to thetemperature of the thermometer.

The emissivity of the conductor is a key variable in determining theconductor temperature with a thermal imaging camera sensor. Theemissivity varies depending on conductor age, type, climate and airquality. Empirical data about conductor emissivity in real-lifeconditions has been published by Rigdon, W. S., House, H. E., Grosh, R.J. and Cottingham, W. B. (1963) “Emissivity of Weathered Conductorsafter Service in Rural and Industrial Environments”. Table 1 below showsthe emissivity values Rigdon, W. S. et. al. reported in industrialatmosphere and Table 2 below shows the reported values in ruralatmosphere. Noticeably, the emissivity values of all conductors withservice age over 1 year was between 0.67 and 0.95. This age class coversalmost all conductors in service at the moment. Additionally, as thefollowing example shows, when the emissivity varies within this range, afairly accurate temperature estimate can be produced just by assumingthe emissivity to be, for example, about 0.8.

TABLE 1 Emis- Conductor Volt- Sample Years sivity Size, MCM † age,Geographical Number Exposed ε (200 F.) or Awg Kv Location 56-10  4 0.84795, 26/7 120 Great Lakes 56-14  4 0.80 795, 26/7 120 Great Lakes 56-16 4 0.80 477, 26/7 120 Great Lakes 56-17  4 0.81 477, 26/7 120 GreatLakes 8-CST* 25 0.89 266.8, SA 120 Great Lakes 57-155  1 month 0.62 500,SA-19 161 Southern states 57-160  2 months 0.83 500, SA-19 161 Southernstates 57-163  5 months 0.93 500, SA-19 161 Southern states 58-2  8months 0.92 500, SA-19 161 Southern states 58-40 10 months 0.91 500,SA-19 161 Southern states 58-6  1 0.94 500, SA-19 161 Southern states57-147  7 0.91 636, 26/7 161 Southern states 57-123 30 0.95 4/0 6/1 120Southern states 5-CST 38 0.77 400, SA-19 161 Southern states 6-CST 230.79 500, 30/19 120 Northeastern states 58-7 41 0.85 500, 30/19 120Northeastern states 57-153  2 0.90 477, 26/7 44 Western states 57-158 5½ 0.80 397 5, SA-19 120 Western states 9-CST 43 0.88 350, SA-19 60Western states All conductors ACSR, or stranded aluminum (SA). *CSTdenotes tests by C. S. Taylor at Alcoa Research Laboratories, NewKensington, Pa.; other samples tested at Purdue University, Lafayette,Ind. † Thousand circular mils.

TABLE 2 Emis- Conductor Volt- Sample Years sivity Size, MCM * age,Geographical Number Exposed ε (200 F.) or Awg Kv Location 57-154  1month 0.53 500, SA-19 161 Southern states 57-159  2 months 0.54 500,SA-19 161 Southern states 57-162  5 months 0.53 500, SA-19 161 Southernstates 59-1  8 months 0.82 500, SA-19 161 Southern states 59-3 10 months0.73 500, SA-19 161 Southern states 59-5  1 0.71 500, SA-19 161 Southernstates 57-133 13 0.95 3/0, 6/1 66 Southern states 57-149 13 0.76 477,26/7 161 Southern states 57-135 17 0.86 3/0, 6/1 66 Southern states57-118 29½ 0.95 500, SA-19 161 Southern states 57-119 29½ 0.85 500,SA-19 161 Southern states 57-150 40 0.87 500, 30/19 161 Southern states57-156  5 0.67 4/0, 6/1 138 Western states 57-157 45 0.74 4/0, SA-7 70Western states All tests run at Purdue University. All conductors eitherACSR or stranded aluminum (SA). * Thousand circular mils.

The following example of imaging conditions illustrate the impact ofemissivity determination accuracy to the thermal analysis accuracy: Letus assume the sky temperature is 49° F., the conductor temperature is54.3° F. and the conductor emissivity is 0.8. However, the emissivityvalue is determined, as described above, to be 0.7. The thermal readingacquired would report conductor temperature of 55° F. Correspondingly,if emissivity was overestimated to be 0.9, the thermal reading would bemeasured to be 53.7° F. As a rule of thumb, error of 0.1 in emissivity,if the conductor emissivity is in range that is typical to seasonedconductors and the sky conditions are in a normal range of non-winterdaytime conditions, will not cause over 5° F. errors in thermalreadings. FIG. 7 presents the temperature measurement error, inFahrenheit degrees, caused by emissivity determination error. In thisfigure, the true emissivity of the conductor is 0.8. However, theemissivity of 0.7 is used to calculate the temperature. The error ofconductor temperature is presented in degrees ° F. as a function of thedifference between sky temperature and true conductor temperature. Intypical spring, summer and autumn daytime conditions, the differencebetween sky temperature and conductor temperature is within −45° F. and+10° F., with sky temperature being typically colder than the conductor.As seen from FIG. 7, this would cause, at maximum, a temperaturemeasurement error of −5° F., if emissivity was estimated 10 percent toolow. It is viable to estimate emissivity to 5 percent error usingmultiple different approaches presented in this document. It is viableto measure the conductor emissivity within 0.05 error, for example, byusing reference of high-emissivity paint markers or even a formula thatutilizes the conductor age, type, climate and air quality conditions. Ifactual emissivity measurements are not available, using an averagedemissivity of, for example, 0.82 will provide adequate results in mostconditions.

Alternatively, if the emissivity value cannot be measured, a model ofemissivity as a function of conductor type, climate, air quality andservice age can be used to improve the emissivity determinationaccuracy. This is done by acquiring emissivity data on the conductorsthat can be accessed, and fitting a model between conductor type,climate, air quality and service age or other predictors that areavailable. A non-parametric determination method (nearest neighbor,k-nearest neighbors etc.) can be used as an alternative to fittedregression model.

Line Modeling with Calculated Conductor Temperatures (74).

The line modeling process itself is well-known to the industry and ispresented, for example, in the following articles: Hooper, Brian,“Vegetation Management Takes to the Air”, Transmission & DistributionWorld, September 2003; and Hooper, Brian & Bailey, Tom, “Aerial SurveysCalculate Vegetation Growth”, Transmission & Distribution World,September 2003. These articles are hereby incorporated by referenceherein.

3D CAD modeling of transmission lines can be done using the LiDARmeasurements. For example, commercially available PLS-CADD® softwarepackage, available from Power Line Systems, 610 N. Whitney Way, Suite160, Madison, Wis. 53705, can be used to model line conductors withLiDAR data.

Transmission structures, conductor location and conductor attachmentpoints are identified. Structures and conductors are modeled to matchthe LiDAR. The as observed-conductor location is often modeled byfitting a wire in the model to match the catenaries of LiDAR returnsfrom conductor for each span. Conductor type, diameter, weight andtemperature are attributed to the model. The temperature is taken fromthe above described temperature determination process.

The sun is a very hot body that can cause reflection effects on overheadimaging, even if the reflectivity is relatively low. Optionally, anarrow-band filter can be used to minimize sun reflections.

The filter may be selected to allow passage of radiation in theabsorption bands of CO2 or H2O, where the atmosphere cuts down theamount of heat radiation from sun.

Additionally, in thermal image frame selection and in thermalmeasurement window selection, the conductor areas with high sunreflection are discarded.

Alternatively, to minimize the sun reflection artifacts, the datacollection can be done at night or under heavy cloud conditions.

Using narrow field of view, sensor vibration can be a serious problem,especially, when the sensor is mounted on a vibrating vehicle such as ahelicopter. There are a few alternative ways to handle this problem withvibration control. An effective solution is to apply all of thevibration control strategies below.

-   -   1. Fast exposure time. The sensitivity of thermal cells varies        by sensor type. For this application, high sensitivity cells are        preferable because they allow short exposure time. The shorter        the exposure, the less vibration effect is seen on the image        frames. Cooled sensors tend to be more sensitive than non-cooled        sensors. An effective solution is to use sensor that allows 3-4        μs exposure.    -   2. Disregard the data with problematic vibration effect.        Typically, vibration of certain frequency follows the pattern        where the speed of object motion varies as a function of time        and can be expressed with a sine—shaped curve. Vibration can be        rotational or translational. Helicopter vibration is a        combination of many rotational and translational frequency        components. Most harmful for the thermal image frame quality is        the vibration 1-10× the exposure time. Typically, the lower is        the vibration frequency, the wider is the amplitude. Because of        the varying speed of the sensor during the vibration cycle, some        thermal image frames have more harmful vibration effect than        others. For conductor measurements, not all thermal image frames        are needed. There is room to disregard the frames with an        excessive vibration effect, which is an effective method of        vibration control. Simply, in this process, frames with        excessive vibration effect are not used. To automatically filter        out the frames with heavy vibration effect a computer program        can be used. The program identifies the image sharpness. If        image sharpness is below a given threshold, the frame is        automatically disregarded. For example, the differences between        neighboring pixel values across the flight direction can be used        to analyze image sharpness. The bigger is the mean of        differences between neighboring pixel values, the sharper the        image.    -   3. The thermal camera can be isolated from the helicopter        vibration using a suspended mount with some counterweight. The        camera can be tightly attached to a counterweight plate that is        shaped to balance the center of gravity to the graphical        centroid of the camera attachment points. This minimizes the        rotational vibration of the camera. Altering the total weight of        the camera- optics- and counterweight package, the nominal        frequency of the mounted camera system can be set to differ from        the typical main frequencies of the helicopter vibration during        thermal collection event.    -   4. The vibration may be controlled by using motion controlled        gyroscopic system. These systems are commercially available and        represent known technology.

Motion blur may also be an issue. The helicopter is often moving at30-60 knots during collection. With typical integration times anddesired resolution, the footprint of a pixel moves quite significantlyduring intergration. For example, 7 ms intergration time and 60 knotspeed causes a pixel to move about 21.5 cm. This could cause the pixelto move over the target area so much that the pixel does not representreduction of any small object. This is called “motion blur”. Since theaircraft movement co-aligns with conductor direction, the pixel that isin the conductor center stays on the conductor center and still is ableto acquire accurate reading of the conductor. If the helicopter movementdeviates from conductor direction, the motion blur prevents measurement.Such frames are easily recognizable as the conductor image is not sharp.The image frames with motion blur are discarded from the analysis.

When discarding of image frames is used as a method of controllingartifacts or areas of no interest, a large amount of imagery needs to beanalyzed for usability. Some automatic methods are presented here toselect the image frames that contain high quality information from theconductor area.

Vibration control using automatic discarding of thermal image frameswith a heavy vibration effect A₁₁ A₁₂ A₁₃ A₁₄ A₁₅ A₁₆ A₂₁ A₂₂ A₂₃ A₂₄A₂₅ A₂₆ A₃₁ A₃₂ A₃₃ A₃₄ A₃₅ A₃₆ A₄₁ A₄₂ A₄₃ A₄₄ A₄₅ A₄₆ A₅₁ A₅₂ A₅₃ A₅₄A_(. . .) A_(. . .) A₆₁ A₆₂ A₆₃ A₆₄ A_(. . .) A_(nm)

The above table represents a 6×6 pixel “thermal image” taken from ahelicopter that moved upwards in the image when the image was captured.Assumption is the sensor was in vibrating conditions during the imageexposure. Additionally, it was assumed that the most harmful vibrationis the one across the flight direction, since the conductor is a longobject along the flight direction, and vibration along the flightdirection will only cause artifacts that mix the conductor pixel valuesto each other. To test the vibration effect on this image, the followingalgorithm can be used:

Image sharpness index S is calculated:

For computational efficiency, the sharpness can be calculated by takingfor example a systematic sample of thirty 5×5 masks over the thermalimage frame. S is calculated for each mask and sum of the S values overthe sample is used.

The algorithm is run for a file folder of image frames. Each image frameis analyzed, and the frames with sharpness above a given threshold aresaved to another folder.

Areas with high thermal emission background may be avoided for betterthermal reading accuracy. If the background is warmer than theconductor, its emission may tamper the thermal reading from theconductor by scattering to the conductor, pixels in the atmosphere.

High thermal readings can be sorted out with an automatic algorithm.Mean pixel value is calculated for the thermal image frame. If the meanvalue is higher than a given threshold, the image frame is discarded.The conductors cover such a small area of the image that their heatsignature will not alter the mean value of the frame significantly.

For computational efficiency, the background thermal emission level canbe calculated by taking, for example, a systematic sample of thirty 5×5masks over the thermal image frame. The mean is calculated as a meanvalue of all pixels in all masks. Calculation of image sharpness andhigh background value can be combined in the same program.

Due to the small footprint and helicopter operation accuracyconstraints, only some of the thermal image frames actually have theconductors covered. The purpose of the conductor filter is toautomatically find the thermal image frames that feature conductors inthe image frame. In the thermal image frames with low thermal backgroundradiation, the conductor typically is among the highest thermal signals.If the conductor causes a heated strip, for example 3 pixels wide acrossthe frame, it can be detected using an automatic pattern matchingalgorithm. A pattern matching filter of FIG. 5 can be applied, wherepixel values in the pixel of the middle strip have to be higher than thepixel values of the side strips.

In the line imaging case, the helicopter heading is known at time ofthermal imaging. The filter direction can be set to find conductors inapproximate flight direction. In this example, the flight direction isfrom left to right. The pixel value in pixel 2 is compared to values inpixels 1 and 3. If pixel 2 value is more than a given threshold t higherthan values in 1 and 3, it is assigned as “positive”. Rows 4 . . . 6, 7. . . 9 and 10 . . . 12 are assessed the same way. If all rows arepositive, the filter center point (identified with a cross) is assignedto contain a conductor. The filter is run from up to down along a givenpixel row. Pixel rows are sampled over the whole image frame, taking forexample every 20th row into analysis and attributingconductor-containing pixels as “conductor locations”. Linear models arefit through all conductor locations found. If any of the linear fitscontains more than threshold of F of the found conductor locations inits close proximity P, the thermal image frame is deemed to contain athermal image of an operating conductor.

When operating the system with multiple widely-spaced conductors, onemust consider that the swath of a sensor at conductor level may be about16-17 ft with 640 pixel sensor array and ⅓ inch resolution. Manytransmission line circuits have wider spacing of phases than 12 ft whichmeans all conductors cannot be collected in one pass. This can beaddressed by, for example, any of three different solutions:

-   -   1. Assuming the loading is the same in all phases of a circuit.        This way, only one phase needs to be sensed. In the case of        double circuits, where different circuits are attached to the        same structures, this approach will not work.    -   2. Using a sensor cell with higher resolution or a set of        multiple sensors running parallel to each other.    -   3. Moving the swath, during a single pass, so that it alternates        the coverage between conductors of interest. This can be done        either by the pilot, moving the helicopter path so that the        sensor points at different conductors during collection, or if        an actively controlled gimbal is used, by the equipment        operator, pointing a gimbaled camera towards different        conductors during the pass.

The embodiments described above may allow remote thermal measurements ofconductor temperature at time of LiDAR data collection and use of suchmeasured conductor temperature, acquired from the direct thermalmeasurements, for power line clearance analysis. Measured thermalreadings allow more accurate temperature information than temperaturesmodeled from ambient conditions and line loading information.

Spatial accuracy of the temperature information is better than theinformation that is derived from ambient conditions and line loading.Each span that has a thermal image can have a measured thermal reading.The added spatial accuracy benefits especially line modeling in variableterrain, like mountains, where the line crosses many differentelevations, wind channels, and other features that impact small-scaleweather. A weather station that is located in horizontal proximity butin different elevation may show different weather conditions.

Additionally, using weather stations, it is difficult to measure theweather conditions on the conductor level. The conductors may experiencesubstantially higher wind than ground level weather station.

The improved accuracy of the conductor temperature measurements isbeneficial, especially when maximum operating temperature or lineclearances are analyzed. High costs may be incurred to improve ormaintain the line rating. Higher measurement precision allows moreaccurate rating and safe operation of the line at its maximum capacity.This is especially critical today, when many lines operate on the upperend of their maximum capacity, and lines are re-built to increase therating.

Vegetation management benefits from improved accuracy in conductor saganalysis. Less vegetation needs to be cut if smaller measurement errormargins can be applied to ensure safe and reliable operation.

This new thermal line analysis technology provides electric utilitieswith the methodology to replace the calculated, or estimated temperatureof their conductors based on weather conditions and line loading withmore precise, actual temperature readings based on thermal measurementsof the conductor. The associated decrease in margin of error enablesutilities to: improve system reliability and capacity; enhance thesecurity of transmission assets; demonstrate compliance with applicableregulatory requirements; and reduce mitigation costs associated withcompliance by as much as $2 billion over a three year period. In recenttesting confirmed by Electric Power Research Institute (EPRI) sensors,the accuracy provided by the present invention presented a 95 percentconfidence level, with residual error of only 3.75° F.

This invention materially contributes to more efficient utilization andconservation of energy resources. It is the only technology today thatcan remotely measure transmission line conductor temperature to within3.5 degrees F. This ability is critical when building LiDAR-based linemodels, which are the basis of today's transmission line maintenance,design, and capacity and safety analysis. Accurate temperatureinformation provides for grid capacity, which is a critical input forenergy efficiency.

The invention also enables enhanced energy conservation by providingmore accurate temperature data which will ensure generation andtransmission assets are better synchronized to meet demand. It alsoallows more efficient use of renewable energy, by optimizing transfercapacity from generation to consumers. This invention enables generatorsto more accurately see the flow of electricity through transmissionconductors, thereby making improvements to the grid where it is mosturgently needed.

Additionally, the invention supplies utilities with precise data toidentify congestion points on the grid. This is a critical input forefficient capital utilization and to enhance reliability. Grid safetyand reliability are major issues in the utility industry. The inventionhas a direct positive impact on power line reliability.

Although specific examples have been described herein, other approaches,apparatus, components and methods may be employed to implement theinvention. For example, the thermal sensor may be situated remote,proximate, or in contact with the conductor to provide direct thermalmeasurements of the conductor substantially simultaneous withacquisition of the 3-dimensional location data.

1. A method of analyzing an overhead electrical conductor, comprising:by a processor, accessing 3-dimensional location data of an overheadconductor; by the processor, accessing thermal measurement data of theconductor, wherein the thermal measurement data comprises a remotelycollected thermal image wherein each element of the thermal measurementdata corresponds an element of the 3-dimensional location data and has acollection time that is substantially simultaneous with a collectiontime of its corresponding location data element; by the processor,generating a computer assisted design (CAD) model of the conductor usingthe 3-dimensional location data of the conductor and the thermalmeasurement data of the conductor; and by the processor, employing thecomputer assisted design (CAD) model for thermal analysis of theconductor.
 2. The method of claim 1 wherein the remotely collectedthermal image comprises a plurality of thermal image frames, and furthercomprising: selecting, for processing, one or more frames of saidthermal image frames that contain the conductor, contain a backgroundhaving lower thermal values than the conductor, and exhibit imagequality that allows accurate thermal reading.
 3. The method of claim 2,further comprising, by the processor, linking a selected frame to ageographic location.
 4. The method of claim 3, further comprising, bythe processor, extracting a thermal reading from the geographicallylinked selected frame.
 5. The method of claim 4, further comprising, bythe processor, determining emitted energy from the conductor inaccordance with the following equation:$W_{obj} = \frac{W_{tot} - {\left( {1 - ɛ} \right) \times \tau \times W_{amb}} + {\left( {1 - \tau} \right) \times W_{atm}}}{\left( {1 - \tau} \right)}$wherein W_(obj) comprises a measure of energy emitted from theconductor, W_(tot) comprises the thermal reading extracted from thegeographically linked selected frame and represents total radiation,W_(amb) comprises reflected emission from ambient sources, W_(atm)comprises emission from an atmosphere, τ comprises transmittance of theatmosphere, and ε comprises emissivity of the conductor.
 6. The methodof claim 1, further comprising acquiring the thermal measurement data ofthe conductor substantially simultaneously with collecting the3-dimensional location data.
 7. The method of claim 1, furthercomprising: performing a thermal analysis of the thermal measurementdata to determine temperature of the conductor at the time that the3-dimensional location data was collected; wherein said computerassisted design (CAD) model of the conductor is generated using atemperature of the conductor determined by the thermal reading; andemploying the computer assisted design (CAD) model of the conductor toanalyze clearance between the conductor and surroundings of theconductor.
 8. The method of claim 7, wherein employing the computerassisted design (CAD) model to analyze clearance comprises conducting atleast one of a sway analysis and a sag analysis to determine conductorlocation in different weather and/or line loading conditions.
 9. Themethod of claim 1, further comprising: performing a thermal analysis ofthe thermal measurement data to determine temperature of the conductorat a time that the 3-dimensional location data was collected; whereinsaid computer assisted design (CAD) model of the conductor is generatedusing the temperature of the conductor determined by the thermalanalysis; and employing the computer assisted design (CAD) model of theconductor to determine a thermal rating of a target line that includesthe conductor.
 10. The method of claim 1, wherein the 3-dimensionallocation data comprises LiDAR data collected from an airborne vehicle,and said thermal measurement is acquired by the airborne vehicleconcurrently with the LiDAR data.
 11. A method for determiningtemperature of an overhead electrical conductor, comprising: by aprocessor, accessing 3-dimensional location data of an overheadconductor; accessing thermal measurement data of the conductor, whereineach element of the thermal measurement data corresponds an element ofthe 3-dimensional location data and has a collection time that issubstantially simultaneous with a collection time of its correspondinglocation data element; and performing a thermal analysis of the thermalmeasurement to determine temperature of the conductor at a time that the3-dimensional location data was collected.
 12. The method of claim 11,further comprising generating a computer assisted design (CAD) model ofthe conductor using the collected 3-dimensional location data of theconductor and the determined temperature of the conductor.
 13. Themethod of claim 12, further comprising employing the computer assisteddesign (CAD) model for at least one of: thermal line analysis of theconductor; thermal rating of a power line that includes the conductor;clearance analysis relative to the conductor; and vegetation managementrelative to the conductor.
 14. A system, comprising: a processor; acomputer-readable medium on which is stored location data and thermalmeasurement data for a plurality of overhead electrical conductors; anda non-transitory computer-readable memory containing programminginstructions that enable the processor to: access 3-dimensional locationdata of a selected one of the overhead electrical conductors; accessthermal measurement data for the selected conductor, wherein eachelement of the thermal measurement data corresponds an element of the3-dimensional location data and has a collection time that issubstantially simultaneous with a collection time of its correspondinglocation data element; and perform a thermal analysis of the thermalmeasurement to determine temperature of the conductor at a time that the3-dimensional location data was collected.
 15. The system of claim 14,wherein the instructions also enable the processor to generate acomputer assisted design (CAD) model of the conductor using thecollected 3-dimensional location data of the conductor and thedetermined temperature of the conductor.
 16. The system of claim 15,wherein the instructions also enable the processor to employ thecomputer assisted design (CAD) model for at least one of: thermal lineanalysis of the conductor, thermal rating of a power line that includesthe conductor, clearance analysis relative to the conductor, andvegetation management relative to the conductor.
 17. The system of claim14 wherein the instructions also enable the processor to: access aremotely collected thermal image comprising a plurality of thermal imageframes, and further comprising: select, for processing, one or moreframes of said thermal image frames that contain the conductor, containa background having lower thermal values than the conductor, and exhibitimage quality that allows accurate thermal reading.
 18. The system ofclaim 17, wherein the instructions also enable the processor to: link aselected frame to a geographic location, and extract a thermal readingfrom the geographically linked selected frame.
 19. The system of claim18, wherein the instructions also enable the processor to determineemitted energy from the conductor in accordance with the followingequation:$W_{obj} = \frac{W_{tot} - {\left( {1 - ɛ} \right) \times \tau \times W_{amb}} + {\left( {1 - \tau} \right) \times W_{atm}}}{\left( {1 - \tau} \right)}$wherein W_(obj) comprises a measure of energy emitted from theconductor, W_(tot) comprises the thermal reading extracted from thegeographically linked selected frame and represents total radiation,W_(amb) comprises reflected emission from ambient sources, W_(atm)comprises emission from an atmosphere, τ comprises transmittance of theatmosphere, and ε comprises emissivity of the conductor.
 20. A method ofanalyzing an overhead electrical conductor, comprising: by a processor,accessing 3-dimensional location data of an overhead conductor; by theprocessor, accessing thermal measurement data of the conductor, whereinthe thermal measurement data comprises a remotely collected thermalimage, wherein each element of the thermal measurement data correspondsan element of the 3-dimensional location data and has a collection timethat is substantially simultaneous with a collection time of itscorresponding location data element; by the processor, generating acomputer assisted design (CAD) model of the conductor using the3-dimensional location data of the conductor and the thermal measurementdata of the conductor.
 21. The method of claim 20, further comprising bythe processor, the computer assisted design (CAD) model is employed forthermal analysis of the conductor.